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Merchandise Data Analyst Jobs in Nebraska (NOW HIRING)

Principal, Data & AI Platform Engineer

Omaha, NE ยท On-site

$109K - $131K/yr

We connect financial institutions, corporations, merchants and consumers to one another millions of ... Analytics & Reporting * Build analytics datasets and semantic layers to support enterprise ...

Utilize data analysis, visual presentation tools, and storytelling techniques to communicate ... Enjoy discounts on retail merchandise, our restaurants, world-class resorts and conservation ...

We help merchants and consumers connect, transact, and complete payments, whether they are online ... This role supports the full eDiscovery lifecycle-from data collection and processing through ...

Merchandiser

Omaha, NE ยท On-site

$16.25 - $19.25/hr

Merchandise soybeans and finished soybean products * Negotiate transactions with suppliers and end ... Research, analyze, and interpret market and industry data * Represent the company at plant ...

Merchandiser

Omaha, NE

$16.25 - $19.25/hr

Merchandise soybeans and finished soybean products * Negotiate transactions with suppliers and end ... Research, analyze, and interpret market and industry data * Represent the company at plant ...

retail data collector

Thedford, NE ยท On-site

$15.25 - $17.75/hr

... analysis, and customer targeting that always hit the mark ... We do this by excelling in four key areas - headquarter selling, retail merchandising, store level ...

... analysis, and customer targeting that always hit the mark ... We do this by excelling in four key areas - headquarter selling, retail merchandising, store level ...

... analysis, and customer targeting that always hit the mark ... We do this by excelling in four key areas - headquarter selling, retail merchandising, store level ...

... analysis, and customer targeting that always hit the mark ... We do this by excelling in four key areas - headquarter selling, retail merchandising, store level ...

$79K - $107K/yr

Analyze historical data and current trends to identify risks and opportunities * Create and oversee ... Partner with Merchants and cross-functional teams to influence assortment strategies and financial ...

$79K - $107K/yr

Analyze historical data and current trends to identify risks and opportunities * Create and oversee ... Partner with Merchants and Planning Operations to secure product by market and influence sizing

We connect financial institutions, corporations, merchants, and consumers to one another millions ... Analyze unstructured data such as text, logs, and system events to identify trends, support root ...

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Merchandise Data Analyst information

What is the difference between Merchandise Data Analyst vs Inventory Analyst?

AspectMerchandise Data AnalystInventory Analyst
Required CredentialsBachelor's in Business, Data Analytics, or related field; proficiency in data toolsBachelor's in Supply Chain, Logistics, or related; strong analytical skills
Work EnvironmentRetail or e-commerce companies; data-driven teamsWarehouses, distribution centers, retail stores
Employer & Industry UsageUsed in retail, fashion, and consumer goods industriesCommon in retail, manufacturing, and logistics sectors
Comparison Search IntentAnalyzing sales data, product performance, and trendsManaging stock levels, replenishment, and supply chain efficiency

The Merchandise Data Analyst focuses on analyzing sales and product data to optimize merchandising strategies, while the Inventory Analyst concentrates on managing stock levels and supply chain operations. Both roles require analytical skills and industry knowledge but serve different aspects of retail operations.

What does a Merchandise Data Analyst do?

A Merchandise Data Analyst is responsible for collecting, analyzing, and interpreting data related to merchandise sales, inventory, and customer behavior. They use this information to identify trends, forecast demand, and make recommendations that optimize product assortments and inventory levels. Their insights help retailers improve sales performance, reduce stockouts and overstocks, and enhance customer satisfaction. Merchandise Data Analysts often work closely with buying, marketing, and supply chain teams to support strategic decision-making.

What are the key skills and qualifications needed to thrive as a Merchandise Data Analyst, and why are they important?

To thrive as a Merchandise Data Analyst, you need strong analytical abilities, a solid understanding of retail operations, and proficiency in data analysis, typically supported by a degree in business, mathematics, or a related field. Expertise in tools such as Excel, SQL, Tableau, and experience with merchandising or inventory management systems is highly valuable. Attention to detail, problem-solving skills, and effective communication are critical soft skills for interpreting data and collaborating with cross-functional teams. These skills ensure accurate insights and recommendations that drive inventory optimization, sales growth, and strategic retail decisions.

How does a Merchandise Data Analyst typically collaborate with merchandising and buying teams to influence product assortment decisions?

As a Merchandise Data Analyst, you will work closely with merchandising and buying teams by providing data-driven insights on sales trends, inventory levels, and customer preferences. Your analyses help inform decisions about which products to stock, discontinue, or promote, ensuring that assortments align with market demand and company goals. Regular meetings and cross-functional projects are common, where you'll present findings and recommendations, making your role highly collaborative and influential in shaping the product mix.
What cities in Nebraska are hiring for Merchandise Data Analyst jobs? Cities in Nebraska with the most Merchandise Data Analyst job openings:
Infographic showing various Merchandise Data Analyst job openings in Nebraska as of July 2026, with employment types broken down into 66% Full Time, 8% Part Time, and 26% Contract. Highlights an 61% Physical, 5% Hybrid, and 34% Remote job distribution.

Principal, Data & AI Platform Engineer

Monitise

Omaha, NE โ€ข On-site

$109K - $131K/yr

Full-time

This job post hasย expired today.ย Applications are no longer accepted.


Job description

Calling all innovators - find your future at Fiserv.

We're Fiserv, a global leader in Fintech and payments, and we move money and information in a way that moves the world. We connect financial institutions, corporations, merchants and consumers to one another millions of times a day - quickly, reliably, and securely. Any time you swipe your credit card, pay through a mobile app, or withdraw money from the bank, we're involved. If you want to make an impact on a global scale, come make a difference at Fiserv.

Job Title

Principal, Data & AI Platform Engineer

About the Role

Design, build, and operate a secure, onpremise analytics and AI platform that unifies transactional data from PostgreSQL, DynamoDB, and other source databases into Snowflake, and applies machine learning, LLMs, and advanced analytics to generate businesscritical reports, insights, and operational efficiencies.

This role owns endtoend technical delivery-from data ingestion and modeling to AIdriven analytics-while ensuring strict data security, governance, and compliance suitable for highly regulated FinTech environments. Public AI services are

not permitted; all AI/ML workloads must run onprem or in private infrastructure.

What You'll Do

Data Platform & Snowflake Engineering

  • Design and implement secure data pipelines to migrate and unify data from PostgreSQL, DynamoDB, and other source databases into Snowflake.
  • Build and optimize ELT/ETL workflows, data models, and schemas in Snowflake for analytics and AI use cases.
  • Own Snowflake performance tuning, cost optimization, clustering, and secure data sharing patterns.
  • Ensure high data quality, lineage, and reconciliation between source systems and Snowflake.

Analytics & Reporting

  • Build analytics datasets and semantic layers to support enterprise reporting, dashboards, and adhoc analysis.
  • Enable selfservice analytics for business and operations teams using governed datasets.
  • Collaborate with product and business stakeholders to define KPIs, metrics, and reporting logic.

Machine Learning & LLM Enablement (OnPrem)

  • Design and deploy onprem ML and LLM solutions for reporting automation, anomaly detection, forecasting, and operational insights.
  • Implement private / selfhosted LLM architectures (e.g., containerized or VMbased) with secure inference pipelines.
  • Develop ML pipelines for feature engineering, training, validation, and inference using enterpriseapproved toolchains.
  • Integrate AI outputs into applications, workflows, and reporting solutions.

Operational Efficiency via AI

  • Implement AIdriven automations for operational efficiencies such as:
    • Automated report generation and narrative insights
    • Data anomaly detection and monitoring
    • Intelligent alerting and triage
    • Workflow optimization and decision support
  • Measure and continuously improve AI model accuracy, performance, and business impact.

Application & API Integration

  • Expose secure APIs and services for data access, analytics, and AI inference.
  • Integrate analytics and AI capabilities with existing Java / Spring Bootbased services and applications.
  • Follow secure API practices, including authentication, authorization, and tokenbased access.

Security, Compliance & Governance

  • Enforce data security, encryption, access controls, and governance across PostgreSQL, Snowflake, and AI platforms.
  • Ensure sensitive FinTech data never leaves approved infrastructure or flows into public AI models.
  • Work closely with security teams to support audits, compliance, and risk remediation.
  • Apply secure coding practices and address findings from SCA and security scanning tools.

What you will need

Data & Analytics

  • Strong SQL expertise with PostgreSQL and Snowflake, Data modeling, performance tuning, and optimization
  • ETL/ELT frameworks and data orchestration tools

AI / ML

  • Handson experience with machine learning pipelines and analyticsdriven ML use cases
  • Experience working with LLMs in private or onprem environments
  • Understanding of prompt engineering, embeddings, vector search, and inference optimization
  • Python for ML, data processing, and analytics

Application Development

  • Experience integrating analytics and AI into enterprise applications
  • Knowledge of microservices and APIdriven architectures

Cloud & Platforms

  • Experience with Snowflake in enterprise environments
  • Handson exposure to cloudnative or private cloud platforms (AWS, onprem, or hybrid)
  • Containerization (Docker, Kubernetes) for AI/ML and analytics workloads

Security & Compliance

  • Strong understanding of secure data handling, encryption, and access control
  • Experience working in regulated environments (FinTech preferred)
  • Familiarity with Secure transactions and audit requirements

What You Will Need to Have (Minimum Qualifications)

  • 8+ years of experience in software engineering, data platforms, or analytics engineering, owning productiongrade systems end to end.
  • Strong expertise in SQL, with handson experience in Snowflake and PostgreSQL, including data modeling, performance tuning, and optimization.
  • Proven experience building and operating secure ETL/ELT data pipelines and analytics platforms at enterprise scale.
  • Handson experience with machine learning and analyticsdriven AI use cases (e.g., anomaly detection, forecasting, reporting automation).
  • Experience working with LLMs in private or onprem environments, including inference pipelines, embeddings, or vector search.
  • Proficiency in Python for data processing, analytics, and ML workflows.
  • Experience integrating analytics and AI capabilities into enterprise applications via APIs and services.
  • Familiarity with microservices and REST APIs, including integration with Java / Spring Boot-based services.
  • Experience deploying workloads in onprem, private cloud, or hybrid environments, including containerized deployments (Docker/Kubernetes).
  • Strong understanding of data security, encryption, access controls, and operating in regulated environments (financial services, FinTech, or similar).
  • Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent practical experience).

Preferred Qualifications

  • Experience designing enterprise analytics platforms enabling governed, selfservice reporting.
  • Handson experience implementing AIdriven operational automation (automated insights, alerting, or decision support).
  • Familiarity with Snowflake cost management, clustering strategies, or secure data sharing.
  • Prior exposure to FinTech, payments, or transactionheavy data domains.
  • Experience collaborating with product, business, and security stakeholders on KPI definition and compliancealigned analytics.
  • Experience working in Agile development environments.

Salary Range

$110,000.00 - $186,000.00

These pay ranges apply to employees in New Jersey and New York. Pay ranges for employees in other states may differ.

It is unlawful to discriminate against a prospective employee due to the individual's status as a veteran.

For incentive eligible associates, the successful candidate is eligible for an annual incentive opportunity which may be delivered as a mix of cash bonus and equity awards in the Company's sole discretion.

Thank you for considering employment with Fiserv. Please:

  • Apply using your legal name
  • Complete the step-by-step profile and attach your resume (either is acceptable, both are preferable).

Our commitment to Equal Opportunity:

Fiserv is proud to be an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, gender, gender identity, sexual orientation, age, disability, protected veteran status, or any other category protected by law.

If you have a disability and require a reasonable accommodation in completing a job application or otherwise participating in the overall hiring process, please contactAskHR.US@fiserv.com. Please note our AskHR representatives do not have visibility to your application status. Current associates who require a workplace accommodation should refer to Fiserv's Disability Accommodation Policy for additional information.

Note to agencies:

Fiserv does not accept resume submissions from agencies outside of existing agreements.Please do not send resumes to Fiserv associates. Fiserv is not responsible for any fees associated with unsolicited resume submissions.

Warning about fake job posts:

Please be aware of fraudulent job postings that are not affiliated with Fiserv. Fraudulent job postings may be used by cyber criminals to target your personally identifiable information and/or to steal money or financial information. Any communications from a Fiserv representative will come from a legitimate Fiserv email address.